In [42]:
# Create a subplot
fig = make_subplots()
# Group data by category
categories = top_score_final['category'].unique()
# Add a trace for each anime title, making bars horizontal
# Start with the first category visible
first = True
for category in categories:
category_df = top_score_final[top_score_final['category'] == category]
category_df.sort_values(by='score', inplace=True)
fig.add_trace(
go.Bar(y=category_df['title'], x=category_df['score'], name=category,
orientation='h', visible=first, marker_color='#df6200') # Set bar color to crimson
)
first = False # Set the rest of the categories to invisible
# Create a dropdown menu
buttons = []
for i, category in enumerate(categories):
button = dict(
label=category,
method="update",
args=[{"visible": [i == j for j in range(len(categories))]}, # Only the selected category is visible
{"title": f"Top Anime by for Genre: {category}"}])
buttons.append(button)
# Update layout for dropdown, axes, and xaxis range
fig.update_layout(
updatemenus=[dict(
active=0, # First category is active
buttons=buttons,
direction="down",
pad={"r": 10, "t": 10},
showactive=True,
x=0.77,
xanchor="left",
y=1.25,
yanchor="top"
)],
title="Top Rated Anime by Genre: Action and Adventure",
xaxis_title="Score",
yaxis_title="Title",
xaxis=dict(range=[8, 10]) # Set the range for x-axis
)
fig.write_html("../../data/plots/top_animes_score.html")
# Show the plot
fig.show()
